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| import gradio as gr | |
| import hopsworks | |
| import subprocess | |
| def vocal_remove(audio): | |
| project = hopsworks.login() | |
| mr = project.get_model_registry() | |
| # model = mr.get_best_model("vocal_remover", "validation_loss", "min") | |
| model = mr.get_model("vocal_remover", version=3) | |
| model_path = model.download() | |
| model_path_pth = model_path + "/vocal_model.pth" | |
| # print("model_path: ", model_path)s | |
| subprocess.run(["python3", "inference.py", "--input", audio, "--pretrained_model", model_path_pth, "--output_dir", "./"]) | |
| return "./Instruments.wav" | |
| iface = gr.Interface( | |
| fn=vocal_remove, | |
| inputs=gr.Audio(source="upload", type="filepath"), | |
| outputs="audio", | |
| title="Vocal Remover", | |
| description="Removes Vocals from song, currently undertrained, fragments of vocals can remain depending on song", | |
| ) | |
| iface.launch() |